Mahout Recommendations on Binary data

I'm a newbie to mahout.My aim is to produce recommendations on binary user purchased data.So i applied item-item similarity model in computing top N recommendations for movie lens data assuming 1-3 ratings as a 0 and 4-5 ratings as a 1.Then i tried evaluating my recommendations with the ratings in the test-data but hardly there have been two or three matches from my top 20 recommendations to the top rated items in test data and no match for most users.

So are my recommendations totally bad by nature or do i need to go for a different measure for evaluating my recommendations ?

Please help me ! Thanks in advance.

Pranay, 2nd yr ,UG student.

I think we answered your question on the mailing list, which was a better place to ask:

I would map all ratings, of all values, to a 1. Practically speaking this is probably more 'accurate'.

Are you using a precision-recall test? they're not terribly informative, though they're about the only thing you can do to evaluate recommendations without ratings. That is, it's testing whether it recommends back already-known items, but, that's not necessarily a good test of whether it's making good recommendations. It could be recommending better stuff and not getting credit.